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Advances In Research On Geological Evaluation Of Compressed Air Energy Storage In Underground Gas Storage Facilities, Jiang Wen, Huang Leqing, Zhang Songhang, Ma Huiying

Coal Geology & Exploration

Background Against the backdrop of achieving peak carbon dioxide emissions and carbon neutrality globally, renewable energy has developed rapidly and is gradually changing the world's energy mix. However, the intermittent and fluctuating nature of photovoltaic and wind power energy is prone to cause grid frequency fluctuations and reduced power supply reliability. Compressed air energy storage (CAES) technology has emerged as the key to the stable operation of the green power grid thanks to its large capacity and low cost.Methods Based on a systematic review of domestic and international literature in recent years, this study organizes the current theoretical and …

Macroscopic Failure Characteristics And Seepage Pattern Of Damaged Goaf-Side Coal Pillars Under Confined Water Accumulation, Liu Weitao, Chen Dongqi, Liu Yuben, Du Yanhui, Zhao Jiyuan

Coal Geology & Exploration

Background The method of supporting roadways using small coal pillars has been widely applied in China. As a result, the stability of goaf-side coal pillars affects mining safety. Resulting from multiple disturbance effects, coal pillars tend to contain various types of damage fractures. The confined water environment in goaves with water accumulation might cause the instability failure of damaged goaf-side coal pillars. Methods To investigate the impacts of the damage fracture structure on coal stability, this study introduced the concept of relatively stable initial damage fractures. Based on the theory of damage mechanics, this study constructed hydro-mechanical-damage (HMD) coupling models …

Pseudo-2d Mt Inversion Technique For Small-Frame Tem And Its Application In Advance Geological Prediction, Han Ziqiang, Wanma Longzhi, Li Xiangfeng, Yang Yongqiang, Zhu Xiaoming, Luo Chengxian, Tang Li

Coal Geology & Exploration

Objective To address the bottlenecks of low computational efficiency and impracticality of multi-dimensional inversion in the advance geological prediction based on the transient electromagnetic method (TEM), this study developed a pseudo-two-dimensional (2D) magnetotelluric (MT) inversion technique for small-frame TEM based on time-frequency transformation. Methods First, this study corroborated the significant similarity between the late-time apparent resistivity derived using small-frame TEM and the Cagniard apparent resistivity in the MT method under the parameters commonly used in advance geological prediction. Then, the optimal time-frequency transformation coefficient (C_TF) was introduced to achieve a rapid conversion from the late-time apparent resistivity …

Cultivating Climate And Culture: New Jersey Principals' Use Of Sel In Pk-12 Schools, Michelle Papa

Theses and Dissertations

The purpose of this qualitative, intrinsic case study is to explore how PK-12 principals in New Jersey perceive their approaches to leadership through their own social and emotional learning (SEL). With growing demands placed on school leaders, the study examines how principals integrate the five SEL competencies (self-awareness, self- management, social awareness, relationship skills, and responsible decision-making) into their leadership practices to positively impact school climate and culture. Through semi- structured interviews and document analysis, ten principals revealed that SEL is not only essential for student and staff well-being but also central to their own leadership development. Findings indicate that …

Rising Costs Of Higher Education In United States And Student Debt, Mona Muzammil, Muzammil Arshad, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

100 years ago, college tuition at prestigious Ivy League colleges such as Harvard and Brown was about $130 per year. Even when adjusted for inflation, today's cost of higher education has increased dramatically to the point where a college education is shifting further out of reach for many Americans. This book explains the essential concepts in the debate regarding the staggering costs of higher education, supplying ten original essays by higher education policy experts, a lively historical narrative that provides context to current issues, and systematic guides to find additional sources of information on the subject.

Written from a historian's …

Spatially Resolved Kinematics Of Slacs Lens Galaxies. I. Data And Kinematic Classification, Shawn Knabel, Tommaso Treu, Michele Cappellari, Anowar J. Shajib, Chih-Fan Chen, Simon Birrer, Vardha N. Bennert

Physics

We obtain spatially resolved kinematics with the Keck Cosmic Web Imager (KCWI) integral-field spectrograph for a sample of 14 massive (11 < log₁₀(M₍★₎/M☉) < 12) lensing early-type galaxies at z ∼ 0.15–0.35 from the Sloan Lens ACS (SLACS) Survey. We integrate kinematic maps within the galaxy effective radius and examine the rotational and dispersion velocities, showing that 11/14 can be classified as slow rotators. The data set is unprecedented for galaxy-scale strong lenses in terms of signal-to-noise ratio (S/N), sampling, and calibration, vastly superseding previous studies. We find the primary contributions to systematic uncertainties to be the stellar template library and wavelength range of the spectral fit. Systematics …

Analytical Characterization Of Artemisinin And Its Derivatives Using High Performance Liquid Chromatography, Electrochemistry Reduction, And Fluorescence, Faraja Ombwayo

Theses and Dissertations

Artemisinin and derivatives were subjected to 37°C and room temperature conditions. When HPLC-UV analysis of both conditions was performed, there were differences in both conditions which suggested that artemisinin and derivatives degrade at 37°C. When artemisinin was electrochemically reduced, new peaks were generated and LC-MS analysis of the reduced artemisinin indicated that either new molecules or molecular reorganization was formed. These electrochemical reduction molecules (products) were deemed analogous to the artemisinin reduction occurring in-vivo after oral administration. Fluorescence analysis of artemisinin and derivatives were performed in the presence of dipyridamole. Dipyridamole intensity was observed to decrease when artemisinin or its …

Probing The Effect Of Peg-Dna Interactions And Buffer Viscosity On Tethered Dna In Shear Flow, Fatema Tuz Zohra, Huda Al-Zuhairi, Jefferson Reinoza, Hyeongjun Kim, Andreas Hanke

Mechanical Engineering Faculty Publications

DNA flow-stretching is a widely employed, powerful technique for investigating the mechanisms of DNA-binding proteins involved in compacting and organizing chromosomal DNA. We combine single-molecule DNA flow-stretching experiments with Brownian dynamics simulations to study the effect of the crowding agent polyethylene glycol (PEG) in these experiments. PEG interacts with DNA by an excluded volume effect, resulting in compaction of single, free DNA molecules in PEG solutions. In addition, PEG increases the viscosity of the buffer solution. By stretching surface-tethered bacteriophage lambda DNA in a flow cell and tracking the positions of a quantum dot labeled at the free DNA end …

In The Pursuance Of A Robust Legal Framework To Address Deepfake Harms: An Analysis Of The Indian Legal Discourse, Jyothsna Gurumurthy

Indian Journal of Law and Technology

A common issue we face in the field of law and technology is the constant game of catch-up that the law is required to play to keep up with advances in technology. Deepfake Technology (primarily based on generative adversarial networks, as explored in this article) exemplifies this game of catch-up and provides a fertile ground for academics and regulators/law makers to explore and understand what it means for a technology regulating law or rule to be robust and enforceable. By examining the judicial handling of deepfake claims within a publicity rights discourse in India, this article suggests the adoption of …

3d-Printable Hydrogel With Rapid Ambient Self-Healing, Anna M. Petre

Research from the Berry Summer Thesis Institute, 2025

Inspired by nature, soft robots composed of compliant (“soft”) materials are well-suited for uncertain, dynamic tasks requiring safe interaction between a robot and its environment. Soft robots with the ability mend minor damage (e.g. perforations, tears) have been enabled by the rapid development of self-healing soft materials. Recently, one of these hydrogel materials (internally dubbed “BeckOHflex”) – made entirely from commercially available precursors – was developed with several appealing characteristics including rapid ambient self-healing, 3D printability on commercial machines, and competitive mechanical properties. However, the self-healing performance of BeckOHflex falls short of competitors that leverage custom-synthesized precursors. This project aims …

Simulating Chemiluminescence Spectra Of Oh Radical Using Quantum Dynamical Simulations, Triet M. Cao

Research from the Berry Summer Thesis Institute, 2025

Chemiluminescence is a phenomenon of light emission that occurs when molecules transition from an excited state to the ground state. This phenomenon is widely utilized in applications ranging from quantifying product yields in chemical reactions to biological imaging and atmospheric chemistry studies. It has also been used in many crucial applications in the scarce conditions of heat and electricity, such as light sources for astronomy discovery or deep-sea diving. A notable example of such reactions is combustion, where highly reactive hydroxyl radicals (OH) are products. These radicals exhibit a chemiluminescence spectrum because of the interaction between their ground state and …

Intelligent Motion Tracking: A Low-Cost Surveillance Framework Using Soc Devices And Sensor Fusion, Aung Myat Khaung, Nicholas Michael Stiffler

Research from the Berry Summer Thesis Institute, 2025

This thesis presents the design and implementation of a lightweight surveillance system capable of realtime motion detection, object tracking, and behavioral history reconstruction in controlled environments. The system uses System-on-Chip devices such as Raspberry Pi boards equipped with NOIR cameras, monocular cameras, and break-beam sensors that work together to detect and track single or multiple moving objects like colored balls. The prototype is validated in structured settings with the goal of eventual deployment in more dynamic environments, addressing the challenge of reliably tracking visually similar objects with minimal distinguishing features. The architecture integrates computer vision with sensor fusion by combining …

Urinary Metabolome Study For Monitoring Prostate Cancer Recurrence Following Radical Prostatectomy., Sabur Badmos, Elizabeth Noriega Landa, Kiana L. Holbrook, George E. Quaye, Xiaogang Su, Wen-Yee Lee

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND/OBJECTIVES: Prostate cancer (PCa) is the most common cancer among males. Approximately 20-40% of patients with clinically localized PCa will present with a biochemical recurrence after a radical prostatectomy (RP), while some will present with recurrent metastasis. Monitoring the disease post-treatment is crucial for detecting a potential cancer recurrence early. Urinary volatile organic compounds (VOCs) have shown potential to detect PCa. However, their application in disease monitoring remains unexplored.

METHODS: A total of 165 urine samples were collected from male adults with biopsy-designated PCa-positive results before (n = 55) and after a RP (n = 55), and with …

Novel Nano-Composite Materials (Nncms) With The Designations J1, J2, And J3 For Removal Several Harmful Ions, Mohammed K. Al-Doseri, Safaa. R. Fouda, Mohamed Mossad, Mahmoud H. Mahmoud

Mansoura Engineering Journal

The most toxic material to the environment is heavy metals. remove heavy metals from wastewater is done by adsorption. Many papers have been done using different materials to take off toxic dangerous ions from wastewater. Noval Nano-composites material (NNCM)as designated as J1, J2, and J3 the most used adsorbents in this study. To conduct the experiments, synthetic wastewater was generated in the lab. Batch experiments were conducted to create the best conditions for removing these ions from the wastewater. The optimum conditions obtained were 90 min optimum contact time, and pH equal seven, optimal NNCM dose was 0.5 g/L achieving …

Can Correction Messages Reduce The Spread Of Fake News On Social Media? The Impact Of Information Updates On The Effectiveness Of Corrections, Kelvin K. King, Diego Escobari

School of Economics and Finance Faculty Publications

Although government agencies and fact-checking organizations issue correction messages to mitigate misinformation dissemination on social media, their efforts have been largely ineffective. Drawing on Information Manipulation Theory (IMT) and information extracted from over 84 million tweets, we examine the impact of correction messages and explore how different information updates affect their effectiveness. Our empirical approach differentiates between subpopulations of correction messages. The results support the existence of two distinct types: correction messages that significantly mitigate the spread of fake news—a 1 percent increase in “effective” messages decreases the spread of fake news by 0.89 percent; and those that amplify the …

A Comparison Of Diving Behavior Of Goose-Beaked And Dense-Beaked Whales From Tagging Studies In Multiple Ocean Basins, Jay Barlow, Robin W. Baird, Janelle Badger, Gregory S. Schorr, Erin A. Falcone, Shannon N. Coates, Peter L. Tyack, Andrew J. Read, Leigh S. Hickmott, John W. Durban, Diane Claridge, Natacha Aguilar De Soto, Daniel Miranda Gonzalez, Fleur Visser, Machiel G. Oudejans, Stacy L. De Ruiter, David A. Sweeney, Brenda K. Rone, Stephanie L. Watwood

University Faculty Publications and Creative Works

Studies of cetacean diving behavior in multiple locations in different ocean basins allow for an assessment of variability within and among populations. We examine foraging dive behaviors of goose-beaked whales (Ziphius cavirostris) and dense-beaked whales (Mesoplodon densirostris) using data from 132 tagged whales in seven locations in the Pacific and Atlantic Oceans and the Mediterranean Sea. Acoustic recording tags are used to identify foraging dives by the presence of echolocation. For other tag types, foraging dives are identified based on maximum dive depth. Five parameters are used to characterize foraging dives: maximum dive depth, foraging dive duration, dive cycle duration, …

Performance Analysis Of Computational Methods For Predicting Protein Function In Rare Diseases, Aichetou Mohamed Sidiya, Hanin Alzaher, Razan Almahdi, Tayeb Brahimi

Effat Undergraduate Research Journal

Protein function prediction is crucial for understanding the underlying mechanisms of rare diseases. With the increasing availability of computational methods including machine learning-based approaches, network-based methods, and sequence-based methods, predicting protein functions has become more accessible. However, it is not clear which of these methods performs better or how they compare to each other in terms of accuracy, efficiency, and scalability. In this study, we evaluate several computational methods for predicting protein functions in rare diseases using key performance indicators (KPIs). We analyze the strengths and weaknesses of each method and provide recommendations for researchers and clinicians interested in using …

Electrical Energy Consumption Forecasting Based On Conventional And Artificial Intelligence Methods: A Comparison, Haya H. Binsalim, Jana Kamal, Salma Badaam, Danah Milyani, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial Intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review and compare the classical techniques and the emerging new AI-based techniques used for forecasting electrical energy consumption in buildings. The findings revealed that the Artificial Neural Network (ANN) model achieved the lowest Mean Absolute Percentage Error (MAPE) of 0.928%. AI-based techniques have many advantages over classical techniques, such as their ability to handle a large amount of data and provide accurate and fast results.

Mapping The Research Landscape Of Covid-19 And Artificial Intelligence Using The Lens Database, Aichetou Mohamed Sidiya, Jailan Fouad Aljizawi

Effat Undergraduate Research Journal

Due to the rapid spread of the COVID-19 pandemic, all countries faced a significant challenge in their efforts to monitor and halt the spread of the virus. Moreover, researchers around the world raced into publishing to get to understand the effects of this pandemic on every aspect of our life whether that was economic, medical, or social. Thus, this research seeks to assess the quality of research on the application of Artificial Intelligence in the Covid-19 pandemic with an emphasis on Saudi Arabia. The research methodology is based on Bibliometric Analysis techniques and VosViewer for various bibliometric visualizations based on …

The Relationship Between Self-Talk And Self Esteem Amongst University Students, Weam Batarfi, Saddiga Al-Ghalib

Effat Undergraduate Research Journal

The theory of self-talk is important to human nature and has the capacity to enhance person's life. In addition, self-esteem plays a major role in mankind life, either in a positive or a negative way. This work was done to analyze the relationship between self-talk and self-esteem among university students. This work was carried out based on quantitative method. For this work, the sample population was university students and the sample size used was 100 students. Data collection was done using survey method. Furthermore, the scales that were used are the Self-Talk Scale development, Factor Analysis, and Validation and self-esteem …

Wideband Spectrum Sensing For Cognitive Radio Using Under-Sampled Successive Approximation Adc, Aziza I. Hussein

Effat Undergraduate Research Journal

The radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling …

Intelligent Energy Management Mechanisms For Electric Vehicles: A Review, Aziza I. Hussein

Effat Undergraduate Research Journal

This paper investigates intelligent methods used for energy management (EM) in Electric Vehicles (EV). The key role of EM in EVs to increase the performance of the vehicle and reduce Fuel Consumption (FC) thus producing less greenhouse effect. However, the used tactics had limitations. An introduced model of Intelligent Energy Management System (IEMS) for Plug-in hybrid electric vehicles (PHEVs) was efficient for FC reduction. Whereas for IEMS Based on Kalman Filtering showed a low percentage of error. While EM using Tags Threshold Admission And Greedy Scheduling improves EV’s performance, but it can only manage energy per one EV. Another model …

Electrical Energy Consumption Forecasting Analysis Based On Conventional And Artificial Intelligence Methods: A Comparison, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review the classical techniques and the emerging new techniques based on AI of the building electrical energy consumption forecasting. The advantages of AI-based techniques over the classical are that AI methods can handle a large amount of data yet gives accurate results, the results can be found very quickly, in addition to AI having the ability to solve complex nonlinear patterns of raw data. This paper will discuss several studies using different models of forecasting based on …

Potential Pitfalls In Visual Models Of Tipping Points - And How To Fix Them, Jonathan Dechert, Svetlana Gurevich, Stefan Heusler

Northeast Journal of Complex Systems (NEJCS)

Visual models play a crucial role in both science and science communication. However, the distinction between mere analogies and mathematically sound graphical representations is not easy and can be misunderstood not only by laypeople but also within academic literature itself. Moreover, even when the graphical representation exactly corresponds to the mathematical model, its interpretation is often far from obvious. In this paper we discuss the potential landscape visualization commonly used for tipping points in the context of nonlinear dynamics and reveal potential pitfalls, in particular when distinguishing bifurcation induced tipping (B-tipping) from noise-induced tipping (N-tipping).

We propose new visualization techniques …

Optimizing K-Prototype Or Scalable Mixed-Data Clustering: A Vectorized Approach To Accelerate Convergence And Accuracy In Big Data, Faten Fagr Alkourdy

Al-Farahidi Expert Systems Journal

The exponential growth of data stored in databases and data warehouses has intensified the demand for advanced analytical tools capable of efficiently extracting actionable insights. Data mining has emerged as a critical methodology for transforming vast datasets into knowledge. However, traditional techniques often face scalability challenges, particularly due to prolonged computational times, which hinder their effectiveness in large-scale applications. This research aims to improve the K-prototypes clustering algorithm to optimize computational efficiency and enhance clustering precision, enabling more effective knowledge discovery. Key modifications involve implementing vectorization techniques to accelerate processing, redesigning the initialization strategy for cluster centers, and refining the …

Intelligent Control Of Wind Turbines: A Neural-Fuzzy Controller For Pitch And Yaw Angle Regulation Under Variable Wind Conditions, Salah Ali Daoud, Samir Ali Amin, Salah Sabeeh Abed Al Kareem

Al-Farahidi Expert Systems Journal

By modifying the pitch and yaw angles of the blades, the study presents a hybrid neural-fuzzy controller for wind turbines that enhances performance in variable wind conditions. The suggested system integrates fuzzy logic (for decision-making) and artificial neural networks (for learning), unlike conventional PID and fuzzy PID controllers, which have trouble with nonlinear dynamics. It employs two stages of control: pitch control at high wind speeds and yaw control at low wind speeds. The hybrid controller performs noticeably better than PID-based techniques, according to MATLAB/Simulink simulations, lowering pitch control error by 40%, stabilizing the system in 0.1 seconds instead of …

Finite Element Simulation Of Composite Rectangular Cantilever Plates, Muhsin J. Jweeg, Dhia Al-Azzawi, Mohammed Abbas, Mohsin Abdullah Al-Shammari

Al-Farahidi Expert Systems Journal

This work concentrates on the application of the finite element simulation and an experimental program for the composite cantilever plates. The mechanical properties of the models were used to manufacture plates with different aspect ratios and thicknesses. The used models include different aspect ratios of carbon fiber materials and Kevlar composites. In the numerical simulation, the ANSYS package was used to simulate the cantilever plates to obtain the natural frequencies and mode shapes using the mechanical properties obtained experimentally for both types of materials. The findings indicate a strong correlation between the plate geometry and the mode shapes. This gives …

A Study Of Rural Health Care For Chronic Care Management Using Machine Learning To Determine Costs, Joanna Maria Keeling

Doctoral Dissertations

Management of diabetes or heart disease may be uniquely challenging for older individuals with multiple chronic conditions[1]. Chronic Care Management would target patients living with comorbidities in Louisiana, who are not receiving sufficient healthcare services and help them receive the care they deserve[2]. This study is aimed at comparing the results of rural Louisiana Medicaid recipients with comorbidities to the National Averages. We will also use Machine Learning to predict Churn and Medical Costs. To help us identify these patients with comorbidities, we decided to use NCQA Quality Measures. We identified several measures from NCQA that we wanted to use, …

The Design Of Coplanar Waveguide Traveling-Wave Kinetic-Impedance Parametric Amplifiers, Jordan Scott Savoie

Master's Theses

Astronomical observations and many physics experiments rely on cryogenic amplifiers for readout. Current sensitivity is limited by the noise figure of high-electronmobility transistor (HEMT) amplifiers, which have proven di!cult to decrease further in recent years. Traveling-wave kinetic-impedance parametric amplifiers (TKIPAs) are an emerging class of amplifiers which have the potential to substantially improve the sensitivity of microwave low-noise amplifiers (LNAs) while also accepting relatively high input powers and amplifying over a wide bandwidth. In this thesis, I present the design, modeling, and testing procedures for coplanar waveguide (CPW) TKIPAs developed by our group at the National Radio Astronomy Observatory. Using …

Structural And Computational Results On Equitably Dissectible Graphs, Ann Wells Clifton

Doctoral Dissertations

This dissertation introduces the class of equitably dissectible graphs — graphs whose vertex set can be recursively partitioned into two parts whose sizes differ by at most one where the two induced subgraphs are connected. In Chapter 2, we show that a graph is equitably dissectible if and only if it has a spanning tree that is equitably dissectible, and we use this result to establish connections between the class of equitably dissectible graphs and Hamiltonian graphs. We also fully characterize the equitably dissectible spiders of the form S3(a) and S3(a, b), identifying a family of unruly spiders that are …